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Challenges of data availability: Analysing the water-energy nexus in electricity generation
Water is paramount for the operation of energy systems, for securing food supply and for the industry and municipalities. Intersectoral competition for water resources can negatively affect water scarce regions by e.g. power plants shutdowns, poor agricultural yields, and lack of potable water. Future economic and population growth as well as climate change is likely to exacerbate these patterns. However, models used for energy system management and planning in general do not properly include water availability which can lead to improper representations of water-energy interlinkages. The paper initially highlights the water usage rates of current technologies within electricity generation and technologies with a potential to reduce water usage, electricity consumption or GHG emissions. Secondly, the paper presents currently available data on current and future projected water resources as well as data on energy statistics relevant to water-energy nexus studies. Thirdly, implementation cases are presented showing examples of water-energy nexus studies for the data presented. Finally, the paper highlights main challenges in studying the linkage between water and energy. We find a substantial gap in the general availability and quality of regional and global data for detailed quantitative analyses and also identify a need for standardization of formats and data collection methodologies across data and disciplines. An effort towards a coordinated, and sustained open-access data framework with energy sector water usage at fine spatio-temporal scales alongside hydro-climatic observation and model data using common forcings and scenarios for future projections (of climate, socio-economy and technology) is therefore recommended for future water-energy nexus studies. © 2019 The Authors
One simulation, different conclusions—the baseline period makes the difference!
The choice of the baseline period, intentionally chosen or not, as a reference for assessing future changes of any projected variable can play an important role for the resulting statement. In regional climate impact studies, well-established or arbitrarily chosen baselines are often used without being questioned. Here we investigated the effects of different baseline periods on the interpretation of discharge simulations from eight river basins in the period 1960–2099. The simulations were forced by four bias-adjusted and downscaled Global Climate Modelsunder two radiative forcing scenarios (RCP 2.6 and RCP 8.5). To systematically evaluate how far the choice of different baselines impacts the simulation results, we developed a similarity index that compares two time series of projected changes. The results show that 25% of the analyzed simulations are sensitive to the choice of the baseline period under RCP 2.6 and 32% under RCP 8.5. In extreme cases, change signals of two time series show opposite trends. This has serious consequences for key messages drawn from a basin-scale climate impact study. To address this problem, an algorithm was developed to identify flexible baseline periods for each simulation individually, which better represent the statistical properties of a given historical period.